Three applications illustrate how companies are beginning to embrace data-driven solutions while establishing a foundation for future initiatives.

The construction business faces a major productivity challenge. While labor productivity in the global economy has increased by an average of 2.8 percent a year over the past two decades, and in manufacturing by an impressive 3.6 percent, the construction sector has registered a mere 1 percent annual improvement. As the capital-project partners responsible for execution, engineering and construction (E&C) firms are well positioned to drive changes that can help close this troubling gap.

To do so, some are turning to data-driven solutions that have already revolutionized many other corners of the economy. These techniques are emerging as vital tools for improving capital project outcomes and reducing risk. By enabling E&C companies to leverage the vast amounts of data they already collect, analytics can uncover critical insights that both speed up and improve the quality of management decisions. In particular, they can help project teams assess market conditions, portfolio composition, and individual project performance.

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Source: McKinsey and Company
This article was originally published by 
McKinsey & Company, www.mckinsey.com. 
Copyright (c) 2021 All rights reserved.

Identify strategies for data-driven use of machine learning and artificial intelligence for Industrialized Construction - Quiz

Identify strategies for data-driven use of machine learning and artificial intelligence for Industrialized Construction - Quiz

AI/ML can help with the following (select all that apply):

Pivotal moments in a project can create risk, such as adding cost, causing delays, or even producing legal issues.

What are some of the major challenges the industry is facing?